Features
Features built for engineering leaders who manage risk and budget.
KodeGauge combines traditional code quality checks with infrastructure intelligence and cost analysis so you can make smarter engineering decisions.
Repository insight
Repository Health Scoring
Get an instant snapshot of your code health across multiple dimensions, not just a single number.
What it does
- Security score (vulnerability & dependency risk)
- Maintainability score (complexity, documentation, test coverage)
- Performance score (throughput, bottleneck severity, scaling readiness)
- Cost efficiency score (infrastructure waste, optimization opportunities)
Visual snapshot
How this feature helps
Security
Measured and translated into actionable engineering signals.
Maintainability
Measured and translated into actionable engineering signals.
Performance
Measured and translated into actionable engineering signals.
Why it matters
Different teams care about different things. Your security team wants risk. Your platform team wants infrastructure limits. Your CFO wants costs. KodeGauge gives each stakeholder a score they understand.
Scaling analysis
Infrastructure Analysis & Bottleneck Detection
Discover what your code is actually configured to do, and where it will break first under load.
What it does
- Detects concurrency models (async/await, threading, worker pools)
- Identifies the primary bottleneck (database, CPU, memory, API rate limits)
- Maps database pool size and average query time
- Estimates throughput capacity with current specs
- Flags memory constraints and headroom
- Detects frontend performance concerns (bundle size, library bloat)
Visual snapshot
How this feature helps
DB pool
Measured and translated into actionable engineering signals.
CPU
Measured and translated into actionable engineering signals.
Memory
Measured and translated into actionable engineering signals.
Why it matters
Most tools tell you if your code is correct. KodeGauge tells you if it will scale. Before you deploy to production and learn the hard way that your database pool is too small, we show you the math.
Client case: A React SPA with unbounded axios concurrency. Database pool set to 10. Average query time 50ms. Our scan showed: Max sustained RPS: 200 req/sec. Primary bottleneck: Database connection pool. Fix: Increase pool size and add request queuing. Estimated new ceiling: 2,000 RPS. Cost impact: $8K/month savings.
Savings model
Cloud Cost Estimation & Savings Analysis
See how much your code costs to run, and how much you could save with improvements.
What it does
- Estimates monthly/annual cloud spend based on current infrastructure
- Calculates cost of infrastructure issues
- Models cost impact of suggested optimizations
- Ranks improvements by ROI
- Tracks cost baseline over time
- Provides per-issue savings estimates
Visual snapshot
How this feature helps
Monthly spend
Measured and translated into actionable engineering signals.
Waste
Measured and translated into actionable engineering signals.
ROI
Measured and translated into actionable engineering signals.
Why it matters
Engineering leaders need to speak the language of business impact. Telling your CEO "we have a database pool inefficiency" means nothing. Telling them "fixing this saves $200K/year" means everything.
A scan revealed: N+1 query patterns: ~$15K/month in wasted database compute. Oversized memory allocation: ~$8K/month. Missing cache layer: ~$30K/month in redundant queries. Total identified opportunity: ~$53K/month. Priority fix (cache layer): Saves $30K/month, 2-week implementation.
Action guidance
AI-Powered Prioritization & Explanation
Move beyond raw findings. Get AI-generated explanations that help you understand what to fix first and why.
What it does
- Generates plain-English summaries of each finding
- Explains business impact (risk, cost, performance)
- Ranks issues by impact and effort
- Shows relationships between issues
- Provides recommended fix approaches
- Estimates effort and time to implement
Visual snapshot
How this feature helps
Impact
Measured and translated into actionable engineering signals.
Effort
Measured and translated into actionable engineering signals.
Priority
Measured and translated into actionable engineering signals.
Why it matters
Developers shouldn't have to interpret raw linter output. Our AI translates findings into actionable context so teams can move fast and make informed decisions.
Finding: High context re-render overhead. AI Explanation: "Your React app re-renders ~200 components per state change. Solution: Split context into smaller, domain-specific contexts. This will reduce re-renders to ~20 per interaction and improve perceived app responsiveness by ~40%." Effort: 3-5 days.
Traffic readiness
Performance Capacity Planning
Know exactly how much traffic your application can handle with current resources, and what it would take to scale.
What it does
- Calculates estimated max sustained RPS with current specs
- Shows database throughput ceiling
- Identifies the critical path to scaling
- Recommends spec changes for target throughput
- Models cost of scaling infrastructure
- Tracks capacity over time as code changes
Visual snapshot
How this feature helps
RPS ceiling
Measured and translated into actionable engineering signals.
Headroom
Measured and translated into actionable engineering signals.
Scale path
Measured and translated into actionable engineering signals.
Why it matters
Before Black Friday breaks your site, you need to know: Can we handle 10K RPS? What would we need to change? How much would that cost? KodeGauge answers these questions.
Current capacity with 4 cores / 8GB RAM / 10 DB conns: Max sustained RPS: ~200 req/sec. To reach 2,000 RPS: Increase DB connections to 50 ($1.2K/month), add Redis ($800/month), increase worker instances ($3K/month). Total added cost: ~$5K/month. New estimated capacity: 2,500 RPS.
Trend visibility
Historical Tracking & Trend Analysis
Track repository health over time and measure the impact of engineering improvements.
What it does
- Maintains scan history for each repository
- Trends health scores and cost baseline over weeks/months
- Shows which improvements had the biggest impact
- Measures technical debt accumulation or reduction
- Identifies patterns (issues that keep recurring)
- Calculates ROI on fixes
Visual snapshot
How this feature helps
History
Measured and translated into actionable engineering signals.
Debt
Measured and translated into actionable engineering signals.
ROI
Measured and translated into actionable engineering signals.
Why it matters
"Are we getting better?" Historical visibility shows whether technical debt is accumulating or decreasing, whether cost-saving efforts are working, and whether quality initiatives are paying off.
Workflow native
GitHub Native Integration
Scan your repositories without leaving your workflow. KodeGauge lives where your code lives.
What it does
- One-click GitHub authentication (no credential storage)
- Scan on demand or on a schedule
- Results available in GitHub Actions
- Integrations with your CI/CD pipeline
- Comments on PRs with findings (optional)
- Programmatic access via API
Visual snapshot
How this feature helps
Auth
Measured and translated into actionable engineering signals.
CI/CD
Measured and translated into actionable engineering signals.
Pull requests
Measured and translated into actionable engineering signals.
Why it matters
Context switching kills productivity. KodeGauge works natively in GitHub so your team doesn't have to jump between tools to see results or take action on findings.
Stack coverage
Multi-Language & Multi-Framework Support
Analyze code regardless of your tech stack.
What it does
- JavaScript / TypeScript, Python, Java, Go, Rust, C#, Ruby, PHP, C/C++
- React, Vue, Svelte (frontend concurrency, state management, re-render patterns)
- Node.js, Python (async patterns, worker models)
- Spring, Django, FastAPI (database patterns, thread pools)
- Docker, Kubernetes configuration analysis
Visual snapshot
How this feature helps
Frontend
Measured and translated into actionable engineering signals.
Backend
Measured and translated into actionable engineering signals.
Infrastructure
Measured and translated into actionable engineering signals.
Why it matters
Most teams use multiple languages and frameworks. You shouldn't need separate tools for each. KodeGauge understands the architectural patterns of your entire stack.
Risk detection
Security & Dependency Risk Detection
Surface vulnerable dependencies and security misconfigurations before they become problems.
What it does
- Identifies known vulnerabilities in dependencies
- Detects outdated libraries
- Flags hardcoded secrets and API keys
- Finds insecure communication patterns
- Checks for licensing compliance issues
- Prioritizes by CVSS severity
Visual snapshot
How this feature helps
Dependencies
Measured and translated into actionable engineering signals.
Secrets
Measured and translated into actionable engineering signals.
Severity
Measured and translated into actionable engineering signals.
Why it matters
You need to know about security risk quickly. KodeGauge integrates security analysis into the repository health picture so you see risk in context with cost and performance.
Delivery planning
Effort Estimation & Fix Recommendations
Know how long a fix will take and how to approach it.
What it does
- Estimates implementation effort (hours or days)
- Provides code examples and reference patterns
- Links to relevant documentation
- Flags prerequisites and dependencies
- Shows related issues that should be fixed together
- Recommends implementation order
Visual snapshot
How this feature helps
Time
Measured and translated into actionable engineering signals.
Dependencies
Measured and translated into actionable engineering signals.
Order
Measured and translated into actionable engineering signals.
Why it matters
Knowing a fix is needed doesn't help if you don't know how much work it is. Our estimates help you schedule engineering work and make trade-off decisions.
Know your code. Control your costs. Reduce your risk.
Get a clear picture of repository health, infrastructure efficiency, and technical debt impact in one scan.
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